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A highly magnified star at redshift 6.2

Naturevolume 603, pages815–818 (2022)Cite this article

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AnAuthor Correction to this article was published on 19 July 2023

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Abstract

Galaxy clusters magnify background objects through strong gravitational lensing. Typical magnifications for lensed galaxies are factors of a few but can also be as high as tens or hundreds, stretching galaxies into giant arcs1,2. Individual stars can attain even higher magnifications given fortuitous alignment with the lensing cluster. Recently, several individual stars at redshifts between approximately 1 and 1.5 have been discovered, magnified by factors of thousands, temporarily boosted by microlensing3,4,5,6. Here we report observations of a more distant and persistent magnified star at a redshift of 6.2 ± 0.1, 900 million years after the Big Bang. This star is magnified by a factor of thousands by the foreground galaxy cluster lens WHL0137–08 (redshift 0.566), as estimated by four independent lens models. Unlike previous lensed stars, the magnification and observed brightness (AB magnitude, 27.2) have remained roughly constant over 3.5 years of imaging and follow-up. The delensed absolute UV magnitude, −10 ± 2, is consistent with a star of mass greater than 50 times the mass of the Sun. Confirmation and spectral classification are forthcoming from approved observations with the James Webb Space Telescope.

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Fig. 1: Labelled colour image of WHL0137-zD1.
Fig. 2: Strong lensing critical curves.
Fig. 3: Lensed star constraints on the H–R diagram.

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Data availability

All HST image data used in this analysis are publicly available on the Mikulski Archive for Space Telescopes (MAST), and can be found throughhttps://doi.org/10.17909/T9SP45 (RELICS) andhttps://doi.org/10.17909/t9-ztav-b843 (HST GO 15842).

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Acknowledgements

The RELICS Hubble Treasury Program (GO 14096) and follow-up programme (GO 15842) consist of observations obtained by the NASA/ESA Hubble Space Telescope (HST). Data from these HST programmes were obtained from the Mikulski Archive for Space Telescopes (MAST), operated by the Space Telescope Science Institute (STScI). Both HST and STScI are operated by the Association of Universities for Research in Astronomy, Inc. (AURA), under NASA contract NAS 5-26555. The HST Advanced Camera for Surveys (ACS) was developed under NASA contract NAS 5-32864. J.M.D. acknowledges the support of project PGC2018-101814-B-100 (MCIU/AEI/MINECO/FEDER, UE) and María de Maeztu, ref. MDM-2017-0765. A.Z. acknowledges support from the Ministry of Science and Technology, Israel. R.W. acknowledges support from NASA JWST Interdisciplinary Scientist grants NAG5-12460, NNX14AN10G and 80NSSC18K0200 from GSFC. E.Z. and A.V. acknowledge funding from the Swedish National Space Board. M.O. acknowledges support from World Premier International Research Center Initiative, MEXT, Japan, and JSPS KAKENHI grant numbers JP20H00181, JP20H05856, JP18K03693. G.M. received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. MARACHAS – DLV-896778. P.K. acknowledges support from NSF AST-1908823. Y.J.-T. acknowledges financial support from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 898633, and from the State Agency for Research of the Spanish MCIU through the ‘Center of Excellence Severo Ochoa’ award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). The Cosmic DAWN Center is funded by the Danish National Research Foundation under grant no. 140.

Author information

Authors and Affiliations

  1. Center for Astrophysical Sciences, Department of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD, USA

    Brian Welch, Dan Coe & Stephan McCandliss

  2. Space Telescope Science Institute (STScI), Baltimore, MD, USA

    Dan Coe, Roberto J. Avila, Jay Anderson & Larry Bradley

  3. Association of Universities for Research in Astronomy (AURA) for the European Space Agency (ESA), STScI, Baltimore, MD, USA

    Dan Coe

  4. Instituto de Física de Cantabria (CSIC-UC), Santander, Spain

    Jose M. Diego

  5. Physics Department, Ben-Gurion University of the Negev, Be’er-Sheva, Israel

    Adi Zitrin

  6. Observational Astrophysics, Department of Physics and Astronomy, Uppsala University, Uppsala, Sweden

    Erik Zackrisson & Anton Vikaeus

  7. Observatório Nacional, Ministério da Ciencia, Tecnologia, Inovaçãoe Comunicações, Rio de Janeiro, Brazil

    Paola Dimauro

  8. Instituto de Astrofísica de Andalucía, Granada, Spain

    Yolanda Jiménez-Teja

  9. School of Physics and Astronomy, University of Minnesota, Minneapolis, MN, USA

    Patrick Kelly

  10. Department of Astronomy, University of Michigan, Ann Arbor, MI, USA

    Guillaume Mahler & Keren Sharon

  11. Institute for Computational Cosmology, Durham University, Durham, UK

    Guillaume Mahler

  12. Centre for Extragalactic Astronomy, Durham University, Durham, UK

    Guillaume Mahler

  13. Research Center for the Early Universe, University of Tokyo, Tokyo, Japan

    Masamune Oguri

  14. Center for Frontier Science, Chiba University, Chiba, Japan

    Masamune Oguri

  15. Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU, WPI), University of Tokyo, Chiba, Japan

    Masamune Oguri

  16. School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA

    F. X. Timmes & Rogier Windhorst

  17. Joint Institute for Nuclear Astrophysics – Center for the Evolution of the Elements, Tempe, AZ, USA

    F. X. Timmes

  18. Department of Astronomy, Steward Observatory, University of Arizona, Tucson, AZ, USA

    Michael Florian & Brenda Frye

  19. Max-Planck-Institut für Astrophysik, Garching, Germany

    S. E. de Mink

  20. GRAPPA, Anton Pannekoek Institute for Astronomy, University of Amsterdam, Amsterdam, The Netherlands

    S. E. de Mink

  21. Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA, USA

    S. E. de Mink & Felipe Andrade-Santos

  22. Department of Physics, University of California, Davis, Davis, CA, USA

    Maruša Bradač & Victoria Strait

  23. Observational Cosmology Lab, NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Jane Rigby & Soniya Sharma

  24. Cosmic Dawn Center (DAWN), Copenhagen, Denmark

    Sune Toft & Victoria Strait

  25. Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

    Sune Toft & Victoria Strait

  26. School of Physics, University of Melbourne, Parkville, Victoria, Australia

    Michele Trenti

  27. ARC Centre of Excellence for All-Sky Astrophysics in 3 Dimensions, University of Melbourne, Parkville, Victoria, Australia

    Michele Trenti

  28. Clay Center Observatory, Dexter Southfield, Brookline, MA, USA

    Felipe Andrade-Santos

  29. Department of Theoretical Physics, University of the Basque Country UPV/EHU, Bilbao, Spain

    Tom Broadhurst

  30. Donostia International Physics Center (DIPC), Donostia, Spain

    Tom Broadhurst

  31. IKERBASQUE, Basque Foundation for Science, Bilbao, Spain

    Tom Broadhurst

Authors
  1. Brian Welch
  2. Dan Coe
  3. Jose M. Diego
  4. Adi Zitrin
  5. Erik Zackrisson
  6. Paola Dimauro
  7. Yolanda Jiménez-Teja
  8. Patrick Kelly
  9. Guillaume Mahler
  10. Masamune Oguri
  11. F. X. Timmes
  12. Rogier Windhorst
  13. Michael Florian
  14. S. E. de Mink
  15. Roberto J. Avila
  16. Jay Anderson
  17. Larry Bradley
  18. Keren Sharon
  19. Anton Vikaeus
  20. Stephan McCandliss
  21. Maruša Bradač
  22. Jane Rigby
  23. Brenda Frye
  24. Sune Toft
  25. Victoria Strait
  26. Michele Trenti
  27. Soniya Sharma
  28. Felipe Andrade-Santos
  29. Tom Broadhurst

Contributions

B.W. identified the star, led the lens modelling and size constraint analysis, and wrote the majority of the manuscript. D.C. proposed and carried out observations, measured photometry and redshifts, and helped analyse size and magnification constraints. J.M.D. performed and analysed microlensing simulations, and contributed to lens model analysis. A.Z., G.M., M.O. and K.S. contributed to the lens model analyses. E.Z. calculated stellar constraints based on observed magnitude and magnification. P.D. and Y.J.-T. calculated stellar surface mass densities used in microlensing analysis. P.K. and R.W. helped compare results and methods to previous lensed star detections and theoretical predictions. F.X.T., S.E.d.M. and A.V. contributed to stellar constraint analysis and interpretation. R.J.A. reduced the HST images. M.B. and V.S. obtained and analysed Spitzer data. All authors contributed to the scientific interpretation of the results and to aspects of the analysis and writing.

Corresponding author

Correspondence toBrian Welch.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks the anonymous reviewers for their contribution to the peer review of this work.Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Photometry of the Sunrise Arc and Earendel.

a, HST photometry with 1σ error bars, SED fit, and redshift probability distribution for the Sunrise Arc using the photometric fitting code BAGPIPES. The arc shows a clear Lyman break feature, and has a photometric redshiftz = 6.24 ± 0.10 (68% CL).b, HST photometry for the full arc (black), clumps 1.1a/b (green/blue), and Earendel (red), with associated 1σ error bars. BPZ yields a photometric redshift ofzphot = 6.20 ± 0.05 (inset; 68% CL), similar to the BAGPIPES result. Clumps 1.1a/b have similar photometry, strengthening the conclusion that they are multiple images. Note both BPZ and BAGPIPES find significant likelihood only between 5.95 < z < 6.55 for the Sunrise Arc.

Extended Data Fig. 2 Lensed star variability across observations.

Earendel has remained consistently bright across 3.5 years of HST imaging. The figure shows WFC3/IR images of the lensed star (circled in green) across four epochs.a,b, Epoch 1 (a) and epoch 2 (b), taken as part of RELICS; they are a sum of the infrared imaging in four filters F105W + F125W + F140W + F160W from each epoch (one orbit each).c,d, Follow-up F110W imaging taken in epoch 3 (c) and epoch 4 (d). One orbit is shown in each, in a more efficient filter than those used for the previous epochs.e, Plot of the original RELICS photometry (blue) compared to the follow-up photometry (orange), each with 1σ error bars. The blue band is the weighted average of the original RELICS infrared fluxes (35 ± 9 nJy, 68% CL), and the orange band is the new F110W flux (49 ± 4 nJy, 68% CL).

Extended Data Fig. 3 Strong lens modelling constraints for WHL0137–08.

a, HST composite image of WHL0137–08, a massive galaxy cluster atz = 0.566 that lenses the Sunrise Arc. Multiple images of the two lensed galaxies used in the lens modelling are marked in cyan and labelled in zoomed outsets. Cluster member galaxies circled in magenta are those freely optimized in both the LTM and Lenstool lens models. Critical curves are shown for the best-fit LTM model. The dashed orange curve is atz = 3.1, the same photometric redshift as multiple image system 2 (shown inb), and the solid red curve is atz = 6.2, the photometric redshift of the Sunrise Arc (system 1, shown inc). The lensed star Earendel lies directly between 1.1a and 1.1b. Note that 1.1c appears fainter than its counter-images 1.1a/b, owing to its lower magnification and that all of these images are unresolved. The galaxies labelled A–E are described in Methods section ‘Lens modelling’. BCG, brightest cluster galaxy.

Extended Data Fig. 4 Size and separation upper limit measurements.

Earendel’s image is spatially unresolved. We manipulate this image, separating it in two or stretching it in place to put upper limits on its magnified radiusR < 0.055″ and distance 2ξ < 0.11″ between two unresolved images. These constraints allow us to calculate constraints on the intrinsic radiusr, distanceD to the critical curve, and magnificationμ for each lens model. Here we show a zoomed region of the arc around Earendel in a 10× super-sampled reconstruction of our HST WFC3/IR F110W image based on eight drizzled exposures. The distances and radius labelled in the diagram are exaggerated for visibility.

Extended Data Fig. 5 Diffuse cluster light measurements.

Stellar surface mass density calculations are performed in the vicinity of the lensed star, within the green boxes shown. The arc and star are masked to avoid contamination, but nearby cluster galaxies are included. This figure shows the HST F110W band image, which is used to define the extent of the lensed arc.

Extended Data Fig. 6 Flux variations expected from microlensing simulations.

Microlensing is only expected to vary the total magnification by a factor of 2–3 over time, consistent with the observed steady flux over 3.5 years.a, The simulated microcaustic network arising from stars and stellar remnants within the lensing cluster. The cluster caustic is the extreme magnification horizontal region near the middle of the image, with individual cusps from microlenses still visible beyond the cluster caustic. We estimate Earendel will move relative to the microlens network at ~1,000 km s−1 in some unknown direction.b, Predicted magnification fluctuations over time arising from this motion in the 1M⊙ pc−2 case (blue) and the 10M⊙ pc−2 case (purple), assuming that the relative motion is at an angle of 45°. Grey bands highlight a factor of 2 (dark) and a factor of 4 (light) change in magnification.c, The likelihood of magnification variations between two observations separated by different times, again for both the 1M⊙ and 10M⊙ pc−2 cases. Note the ‘more is less’ microlensing effect that reduces variability in the observed images when the density of microlenses increases.

Extended Data Fig. 7 H–R diagrams with stellar tracks at multiple metallicities.

a–d, A star’s metallicity will affect its evolution, so to probe this effect we show here our luminosity constraints compared to stellar tracks from BoOST at metallicities of 1Z⊙ (a), 0.1Z⊙ (b), 0.02Z⊙ (c) and 0.004Z⊙ (d). The 0.1Z⊙ case is also shown in Fig.3, and these plots are similar, including the green region allowed by our analysis. Although the tracks do exhibit some notable differences, the resulting mass estimates do not change significantly given the current large uncertainties.

Extended Data Fig. 8 Stellar evolution tracks versus time.

Here we show the total magnification required to lens stars to Earendel’s apparent magnitude as a function of time on stellar evolution tracks (BoOST 0.1Z⊙, as plotted in the H–R diagram Fig.3). This required magnification changes over the lifetime of each star as it varies in luminosity or temperature, changing the flux observed in the F110W filter. We find that stars at ~100M⊙ and above spend the most time (~2 Myr) in the green region that reproduces Earendel’s observed flux, given our magnification estimates. But considering that lower-mass stars are more numerous, we conclude that masses of roughly (50–100)M⊙ are most likely if Earendel is a single star.

Extended Data Table 1 Hubble imaging of WHL0137–08 in nine filters and photometry measured for the Sunrise Arc and Earendel
Extended Data Table 2 Stellar surface mass densities from two possible IMFs

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Welch, B., Coe, D., Diego, J.M.et al. A highly magnified star at redshift 6.2.Nature603, 815–818 (2022). https://doi.org/10.1038/s41586-022-04449-y

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